The Fog Time Series Anomaly Detection (FTSAD) is a suite of datasets collected on a Raspberry Pi 4B compute cluster. The cluster consists of five 4GB versions and five 8GB versions. We ran the DeFog benchmark applications [1]}, specifically the Yolo, PocketSphinx and Aeneas workloads. We use a random scheduler and execute these tasks as Docker containers [2]}.
We use an existing fault injection module [3]} to create different fault types like CPU overload, RAM contention, Disk attack and DDOS attack. In a CPU overload attack, a simple CPU hogging application is executed that create contention of the compute resources. In RAM contention attack, a program is run that performs continuous memory read/write operations. In disk attack, we run the IOZone benchmark that consumes a large portion of the disk bandwidth. In DDOS attack, we perform several invalid HTTP server connection requests causing network bandwidth contention. We use \(Poisson(5)\)  distribution with faults being sampled uniformly at random from the attack set. More details are given in [3]}.
